Project Summary/Abstract We propose to develop a practical system, designed for daily, in-community use, that detects the occurrence of freezing of gate (FOG) and triggers external cueing stimuli to unfreeze the user. Significance: Parkinson's disease (PD) affects more than one million Americans and its prevalence is expected to double by 2040[15]. Many symptoms of PD become resistant to pharmacological or neurosurgical treatments and therefore become dominant factors affecting quality of life. Among the most treatment-resistant motor symptoms is freezing of gait (FOG). This symptom affects more than 30% of all patients with PD and is characterized by episodic impairments in the ability to initiate gait and the spontaneous arrest of movement during stepping. Incidence of FOG increases with severity and duration of PD with 80% of severely affected patients reporting freezing. Clinicians have long recognized that one of the best methods to facilitate movement initiation in patients with FOG symptoms is to provide them with a sensory cue (e.g. visual, acoustic, or somatosensory). Recently studies have shown that self-triggered cues (e.g. via button press, as is done in most commercially available cueing systems), ineffective in improving gait initiation but that exogenously presented cues reduce the incidence of an inappropriate gait initiation sequences from 20% to less than 1% and increase the magnitude of force generation during stepping increases by an average of 45-71%. Hypothesis: It is hypothesized that through the novel combination of commercially available sensors and custom software, the proposed system will be able to identify FOG episodes in users and provide a sensory cue to facilitate movement thereby minimize the impact of FOG symptoms on quality of life. Specific Aims: The following aims are proposed: 1. Develop a prototype electronics and mechanical packaging in a comfortable / easy to use form factor appropriate for use by individuals with PD; 2. Perform in-lab testing of system performance and safety; 3. Design & implement FOG Detection Algorithms; 4. Evaluate the prototype system in-lab and in- community.